Wang Qiulong, Lv Juantao, Chen Dongdong, Yang Xiaojun
The First Clinical Medical School, Lanzhou University, Lanzhou City, Gansu Province, China.
The Department of Pharmacy, Gansu Provincial Hospital, Lanzhou City, Gansu Province, China.
Ren Fail. 2024 Dec;46(2):2424468. doi: 10.1080/0886022X.2024.2424468. Epub 2024 Dec 4.
Renal impairment is a common outcome of acute pancreatitis. Nevertheless, research on predictive models for major adverse kidney events within 30 days (MAKE30) in acute pancreatitis (AP) has been scarce.
A retrospective study was conducted at Gansu Provincial Hospital, involving 391 patients with acute pancreatitis who were categorized into non-MAKE30 (320 cases) and MAKE30 (71 cases) groups. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors for MAKE30 in the aforementioned patient cohort. The nomogram was developed utilizing findings from a multivariate logistic regression analysis. Subsequent evaluation of the nomogram involved the use of receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis. Additionally, subgroup analyses were performed to different AP etiology and assess secondary outcomes.
Gender, respiratory rate (RR), creatinine (Cr), interleukin 6 (IL-6), prothrombin time (PT), and cardiovascular disease (CVD) were identified as associated predictors of Major Adverse Kidney Events within 30 days (MAKE30) in patients with acute pancreatitis. A nomogram model was developed based on these predictors. Evaluation using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses (DCA) demonstrated that the nomogram model exhibited significant discrimination (AUC = 0.842) > the SOFA score (AUC = 0.809), excellent calibration, and substantial clinical utility. Subgroup analysis showed the nomogram model provided good predictive value for both secondary outcomes and various etiologies.
This model shows promise in efficiently and accurately evaluating the risk of developing MAKE30 in acute pancreatitis patients within the first 24 h of hospitalization.
肾功能损害是急性胰腺炎的常见结局。然而，关于急性胰腺炎（AP）患者30天内主要不良肾脏事件（MAKE30）预测模型的研究却很少。
在甘肃省人民医院进行了一项回顾性研究，纳入391例急性胰腺炎患者，分为非MAKE30组（320例）和MAKE30组（71例）。进行单因素和多因素逻辑回归分析，以确定上述患者队列中MAKE30的独立危险因素。利用多因素逻辑回归分析结果绘制列线图。随后对列线图进行评估，包括使用受试者工作特征（ROC）曲线、校准曲线和决策曲线分析。此外，还对不同的AP病因进行了亚组分析并评估次要结局。
性别、呼吸频率（RR）、肌酐（Cr）、白细胞介素6（IL-6）、凝血酶原时间（PT）和心血管疾病（CVD）被确定为急性胰腺炎患者30天内主要不良肾脏事件（MAKE30）的相关预测因素。基于这些预测因素建立了列线图模型。通过受试者工作特征（ROC）曲线、校准曲线和决策曲线分析（DCA）评估表明，列线图模型具有显著的区分度（AUC = 0.842）>序贯器官衰竭评估（SOFA）评分（AUC = 0.809），校准良好，具有较高的临床实用性。亚组分析表明，列线图模型对次要结局和各种病因均具有良好的预测价值。
该模型有望在住院后24小时内有效且准确地评估急性胰腺炎患者发生MAKE30的风险。
